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80 Cards in this Set
- Front
- Back
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Ethics |
-relate to the principles of right and wrong -codes of ethics -moral standards |
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Predominant ethics philosophies |
-teleology/utilitarianism -deontological |
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Teleology/utilitarianism |
-based on consequences -J. Locke |
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Deontology |
-rule-based -I. Kant |
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Unethical research examples |
-Nuremburg Medical Studies -Tuskegee Syphilis Study |
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Experimental conduct codes |
-Nuremburg Codes -Helsinki Declaration of 1964 -Belmont Report |
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Belmont Report |
-respect for human dignity -beneficence -justice |
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Beaumont and Childress |
-autonomy -nonmaleficence -beneficence -justice |
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Ways to ensure that research is ethical |
-follow professional association guidelines -obtain Institutional Review Board (IRB) approval |
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Researchers must inform participants about |
-purpose -ability to decline -consequences -factors -benefits -confidentiality -incentives -contact |
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Protecting human rights in sport management |
-purpose -ability to decline/volunteer -consequences -anonymity -protection from harm -self-determination -disclosure -privacy |
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Elements of an informed consent form |
-invitation -purpose -demographics -confidentiality -procedure -risks & benefits -alternatives -financial -questions -disclaimer -disclosure |
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Classical levels of measurement |
-nominal -ordinal -interval -ratio |
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Nominal |
-data are given names or categories -mutually exclusive -least quantifiable |
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Ordinal |
-data are given names or categories -not mutually exclusive, but are ordered -only indicate more-or-less relationship; unequal distances |
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Interval |
-data are given names or categories -not mutually exclusive, but are ordered -meaning beyond indicating more-or-less relationship; equal distance -no inherent starting point |
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Ratio |
-data are given names or categories -not mutually exclusive, but are ordered -meaning beyond indicating more-or-less relationship; equal distance -no inherent starting point -most quantifiable |
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Measurement criteria in sport management research |
-reliability -validity |
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Reliability |
-stability -equivalence -internal consistency |
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Reliability as stability |
-same test to same person over time -test-retest -intra-rater reliability |
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Reliability as equivalence |
-equivalent test to same person over time -parallel form -inter-rater reliability |
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Reliability as internal consistency |
-instrument dependability -alpha coefficient**, split-half, odd-even, KR20 |
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Validity |
-face -content -criterion -construct |
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Validity as face/content |
-panel of experts determine if test is measuring what it should be -CVR = (n-N/2)/(N/2) |
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Validity as criterion |
correlation between new scale of measurement and trait |
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Validity as construct |
relationship between measures |
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Does reliability equal validity? |
It is a pre-condition, but no
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Attitude |
enduring disposition to respond consistently |
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Components of attitudes |
-cognitive -affective -behavioral |
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Measurement techniques in attitude research |
-rating -ranking |
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Semantic differential scale |
-affective component -words rather than numbers |
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Likert scale |
-affective component -summated to produce an index |
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Questionnaire development process |
-define the objectives -decide a format -write the questions -review the questionnaire -pretest the questionnaire -revise and finalize the questionnaire -gather data -analyze data |
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Writing the questions |
-criteria -choice order -dealing with don't know or n/a responses |
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Double-barreled question |
Measuring two things in one question by use of the word "and" |
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Leading questions |
Questions leading participants to choose an answer they think is right, e.g. "Don't you think...?" |
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Prestige bias |
Respondents answer questions to feel better about themselves |
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Branching |
An answer to one question leads to another |
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Questionnaire flow |
-gain interest -general -most thought-out -sensitive/demographics |
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Approaches to sampling |
-non-probability -probability |
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Non-probability sampling |
-advantage - less time and money -disadvantage - no way to analyze the probability for selection; less sophisticated -purposive -convenience** -quota |
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Probability sampling |
-every unit has an equal chance of selection -advantage - more accurate representation -disadvantage - more time and money |
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Data preparation and analysis process |
-validating -editing -coding -data entry and analysis |
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Validating |
-confirm data collection took place -survey measured what it needed to -10-20% participants to be contacted |
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Editing |
-questionnaires filled out properly and completely -field -central |
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Field editing |
-first stage -data is accurate, complete, and usable |
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Central editing |
-no ambiguity |
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Editing process involves |
-verification -completeness -consistency -accuracy -missing by logic -missing by design -missing item -refusal to respond -don't know -inadequate response |
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Coding
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assigning numeric codes to responses |
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Coding process involves |
-list all responses -review responses -assign numeric code |
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Coding principles |
-sufficiency -appropriateness -exclusiveness -single-dimensionality |
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Statistics |
-extract units of information from numerical data -descriptive -inferential -parametric -nonparametric |
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Descriptive statistics |
summarize large volumes of data |
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Inferential statistics |
draw conclusions about a large volume of data |
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Parametric statistics |
-conclusions about a population normally distributed, equal variance -interval or ratio |
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Nonparametric statistics |
-determines relationship -ordinal or nominal |
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Null hypothesis |
-H0 -no differences between variables |
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Alternative hypothesis |
-Ha -statistically significant difference between variables |
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Directional hypothesis |
-Hd -alternative hypothesis -identifies where or under what conditions the difference will occur |
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Research questions |
-difference -relationship |
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Difference research questions |
comparing differences between two or more groups |
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Relationship research questions |
-mathematical equation is used -assesses the degree of relationship |
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Statistical significance |
extremely unlikely to have happened by chance (p<.05) |
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Data analysis techniques |
-Describing statistical data as frequency distributions -...as graphic presentations -...by measure of central tendency -...by measure of variability -...by measure of relative proportions |
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Describing statistical data as frequency distributions |
-determine the number of groups or classes -establish the width of each class grouping -determine the class boundaries for each class -count the number of values in each of the class intervals |
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Describing statistical data by graphic presentations |
-bar graph (nominal) -histogram (ordinal, interval, and ratio) -frequency polygon (interval and ratio) -pie chart (nominal) |
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Describing data by measures of central tendency |
-mean -median -mode |
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Describing data by measures of variability |
-range -variance -standard deviation |
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Describing data by measures of relative proportions |
-percentile -percentile range |
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Factors affecting the selection of a communication method |
-setting -audience -writing standards -time for oral -space for written |
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Types of reporting |
-briefing -short -long |
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Briefing |
-intro -findings & conclusion -recommendations |
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Short report |
5-10 pages |
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Long report |
follows a specific writing manual |
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Sections of research report |
-intro -info -methodology -findings -conclusions -recommendations |
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Research reports consist of |
-foreword/preface -cover letter -title page -executive summary -abstract -introduction -review -methodology -findings & discussion -recommendations -references -tables, figures, and charts -appendix/exhibits |
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Poster presentation size |
4x6 |
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Oral presentation size |
10-50 people |
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APA requires what as far as language? |
bias-free |
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Styles of writing |
-APA -MLA -Chicago Manual of Style |
